LLM Context Optimizer - Package Files & Code for AI Prompts
Providing multiple files and context to an AI assistant often degenerates into messy, unstructured copy-pasting where file paths and boundaries get mixed up. This optimizer standardizes multi-file context injection by structuring files with distinct markdown fences, file path headers, and optional tree representations, reducing hallucinations and preventing model confusion.
When to Use This Tool
- Full-Stack Bug Debugging: Package frontend UI code, backend route handlers, and database schema into a single cohesive prompt.
- Project Context Onboarding: Feed full directory trees and architectural overview files to Claude or GPT-4o for deep refactoring.
- Code Review & Security Auditing: Format multi-module PR files for automated vulnerability inspection by LLMs.
- Token-Waste Reduction: Strip comments, excess whitespace, and empty lines to conserve context window capacity.
How to Use
- Add Files: Paste file paths and source code content for each module you wish to include.
- Configure Tree: Optionally specify project directory tree structure to provide spatial architectural context.
- Select Formatting Options: Enable comment stripping or XML tag encapsulation based on target model (Claude vs GPT).
- Copy Optimized Prompt: Copy the compiled single-prompt bundle and paste it directly into your AI chat interface.
Input & Output Example
Input:
File: src/auth.ts (code)
File: src/routes.ts (code)
Output:
### Project Context
```typescript:src/auth.ts
export function verifyToken() { ... }
```
```typescript:src/routes.ts
import { verifyToken } from "./auth";
```
Frequently Asked Questions (FAQ)
Q. Why is structured formatting important for LLMs?
A. Modern models are trained to parse structured delimiters like markdown code fences and XML tags. Clear file path annotations dramatically reduce attribution errors where the AI confuses which function belongs to which file.
Q. Does this compress code to save tokens?
A. It eliminates redundant whitespace, normalizes indentation, and offers optional comment stripping to keep prompt density high without compromising code readability.
Q. Is my proprietary codebase uploaded anywhere?
A. No. All packaging and text manipulation happens entirely inside your browser JavaScript runtime.
Engineering & Privacy Notes
- Supports standard markdown syntax and XML-based prompt conventions recommended by Anthropic.
- Runs completely offline on your device with zero server persistence.
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